This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise.
Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution using iterative Jacobian method instead of using centralized schemes. A totally asynchronous distributed power allocation for sumrate maximization on cognitive GMACs is suggested. Simulation results show that this distributed algorithm for power allocation converges to a fixed point and the solution achieves almost the same performance as the exhaustive search.
S. Han, H. Kim, Y. Han, J. M. Cioffi, and V.C.M. Leung, “A Distributed Power Allocation Scheme for Sum-Rate Maximization on Cognitive GMACs,” IEEE Trans. Commun., vol. 61, no. 1, pp. 248–256, Jan. 2013.